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1.
Physiol Meas ; 44(12)2023 Dec 11.
Article in English | MEDLINE | ID: mdl-37995382

ABSTRACT

Objective.This study aimed to develop an automatic and accurate method for severity assessment and localization of coronary artery disease (CAD) based on an optically pumped magnetometer magnetocardiography (MCG) system.Approach.We proposed spatiotemporal features based on the MCG one-dimensional signals, including amplitude, correlation, local binary pattern, and shape features. To estimate the severity of CAD, we classified the stenosis as absence or mild, moderate, or severe cases and extracted a subset of features suitable for assessment. To localize CAD, we classified CAD groups according to the location of the stenosis, including the left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA), and separately extracted a subset of features suitable for determining the three CAD locations.Main results.For CAD severity assessment, a support vector machine (SVM) achieved the best result, with an accuracy of 75.1%, precision of 73.9%, sensitivity of 67.0%, specificity of 88.8%, F1-score of 69.8%, and area under the curve of 0.876. The highest accuracy and corresponding model for determining locations LAD, LCX, and RCA were 94.3% for the SVM, 84.4% for a discriminant analysis model, and 84.9% for the discriminant analysis model.Significance. The developed method enables the implementation of an automated system for severity assessment and localization of CAD. The amplitude and correlation features were key factors for severity assessment and localization. The proposed machine learning method can provide clinicians with an automatic and accurate diagnostic tool for interpreting MCG data related to CAD, possibly promoting clinical acceptance.


Subject(s)
Coronary Artery Disease , Magnetocardiography , Humans , Coronary Artery Disease/diagnostic imaging , Magnetocardiography/methods , Constriction, Pathologic , Machine Learning
2.
J Opt Soc Am A Opt Image Sci Vis ; 38(5): 628-633, 2021 May 01.
Article in English | MEDLINE | ID: mdl-33983267

ABSTRACT

We propose a new method for band structure calculation of photonic crystals. It can treat arbitrarily frequency-dependent, lossy or lossless materials. The band structure problem is first formulated as the eigenvalue problem of an operator function. Finite elements are then used for discretization. Finally, the spectral indicator method is employed to compute the eigenvalues. Numerical examples in both TE and TM cases are presented to show the effectiveness. There exist very few examples in literature for the TM case, and the examples in this paper can serve as benchmarks.

3.
J Opt Soc Am A Opt Image Sci Vis ; 26(1): 156-62, 2009 Jan.
Article in English | MEDLINE | ID: mdl-19109612

ABSTRACT

We consider the numerical scattering of plane waves by a metallic diffraction grating with a single defect. Besides different diffracted orders, a perturbed scattered field with arbitrary reflection direction is generated by the defect. We transform the diffraction grating into a closed waveguide by introducing a perfectly matched layer. The diffracted field is solved by applying pseudoperiodic boundary conditions on cell boundaries. Then we take two steps to resolve the perturbed scattered field. On the defect cell it is obtained by solving the governing wave equation with absorbing boundary conditions derived by a fast recursive doubling procedure. On the rest of the domain the perturbed scattered field is computed by using the recursive matrix operators efficiently. An optical theorem is employed to evaluate the proposed method.

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